"""
# Chatbot
A way to create a chatbot using OpenAI's GPT-4 API, but using your locally running ollama server
On OSX make sure you run:
launchctl setenv OLLAMA_ORIGINS "*"
See https://github.com/ollama/ollama/blob/main/docs/faq.md#how-do-i-configure-ollama-server for
details
"""
import os
from typing import List, cast
from openai import AsyncOpenAI
from openai.types.chat import ChatCompletionMessageParam
from typing_extensions import TypedDict
import solara
import solara.lab
class MessageDict(TypedDict):
role: str # "user" or "assistant"
content: str
messages: solara.Reactive[List[MessageDict]] = solara.reactive([])
model = solara.reactive("llama2-uncensored")
openai = AsyncOpenAI(
base_url='http://localhost:11434/v1/',
api_key='ollama', # shouldn't matter
)
def no_api_key_message():
messages.value = [
{
"role": "assistant",
"content": "No OpenAI API key found. Please set your OpenAI API key in the environment variable `OPENAI_API_KEY`.",
},
]
@solara.lab.task
async def promt_ai(message: str):
if openai is None:
no_api_key_message()
return
messages.value = [
*messages.value,
{"role": "user", "content": message},
]
# The part below can be replaced with a call to your own
response = await openai.chat.completions.create(
model=model.value,
# our MessageDict is compatible with the OpenAI types
messages=cast(List[ChatCompletionMessageParam], messages.value),
stream=True,
)
# start with an empty reply message, so we render and empty message in the chat
# while the AI is thinking
messages.value = [*messages.value, {"role": "assistant", "content": ""}]
# and update it with the response
async for chunk in response:
if chunk.choices[0].finish_reason == "stop": # type: ignore
return
# replace the last message element with the appended content
delta = chunk.choices[0].delta.content
assert delta is not None
updated_message: MessageDict = {
"role": "assistant",
"content": messages.value[-1]["content"] + delta,
}
# replace the last message element with the appended content
# which will update the UI
messages.value = [*messages.value[:-1], updated_message]
@solara.component
def Page():
solara.InputText("ollama model", model)
with solara.Column(
style={"width": "100%", "height": "50vh"},
):
with solara.lab.ChatBox():
for item in messages.value:
with solara.lab.ChatMessage(
user=item["role"] == "user",
avatar=False,
name=model.value if item["role"] == "assistant" else "User",
color="rgba(0,0,0, 0.06)" if item["role"] == "assistant" else "#ff991f",
avatar_background_color="primary" if item["role"] == "assistant" else None,
border_radius="20px",
):
solara.Markdown(item["content"])
if promt_ai.pending:
solara.Text("I'm thinking...", style={"font-size": "1rem", "padding-left": "20px"})
solara.ProgressLinear()
solara.lab.ChatInput(send_callback=promt_ai, disabled=promt_ai.pending)